Following my post yesterday on the "SaaS Illusion," several of you reached out to ask about a specific point: Reusability.
I’ve spent the last year diving deep into this concept with my teams at ATES, specifically within the Dunewind project. Here is the reality: most companies are building AI solutions with disposable outcomes.
When you use AI in your SME to build or deliver a service, you cannot afford to "throw it away" and start from scratch every time. If you do, you’re trapped in a cycle of:
- Constant re-generation of results (solving the same problem twice).
- Endless token consumption.
- Skyrocketing GPU costs that eat your ROI alive.
The solution? Start compounding with Intelligent templates.
This shift toward reusability aligns directly with better business plans and long-term sustainability; it transforms AI from a volatile expense into a predictable asset.
At Dunewind, we have implemented reusability through:
- Building modularly: Create intelligence units that solve specific problems, then re-use them dynamically.
- Stopping the token leak: If a task has been solved once, the logic should be distilled into a smaller, cheaper model.
- Questioning the LLM: Just because you can use an LLM for every step doesn't mean you should. Reusability often means moving from a high-cost model to a low-cost, dedicated module.
What’s your strategy for keeping AI costs under control? Contact us if you'd like to know more about Dunewind and intelligent templates.